TeTRA-VPR: A Ternary Transformer Approach for Compact Visual Place Recognition
Published in arXiv preprint, 2025
This paper introduces TeTRA, a ternary transformer approach that progressively quantizes Vision Transformers to achieve significant reductions in memory consumption and inference latency, while preserving or even enhancing visual place recognition performance on resource-constrained platforms.
Recommended citation: Grainge, O., Milford, M., Bodala, I., Ramchurn, S. D., & Ehsan, S. (2025). "TeTRA-VPR: A Ternary Transformer Approach for Compact Visual Place Recognition." arXiv preprint, arXiv:2503.02511. doi:10.48550/arXiv.2503.02511
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